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FYI - thought some of you might be interested.</div>
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<div id="divRplyFwdMsg" dir="ltr"><font face="Calibri, sans-serif" color="#000000" style="font-size:11pt"><b>From:</b> ACCESS-ANNOUNCEMENTS <access-announcements@ACM.ORG> on behalf of Shari Trewin <trewin@US.IBM.COM><br>
<b>Sent:</b> Friday, April 10, 2020 12:40 PM<br>
<b>To:</b> access-announcements@ACM.ORG <access-announcements@ACM.ORG><br>
<b>Subject:</b> Call for Papers - TACCESS Special Issue on AI Fairness and People with Disabilities</font>
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<p><b><font size="5">Call for Papers - Special Issue of ACM Transactions on Accessible Computing (TACCESS) on AI Fairness and People with Disabilities</font></b></p>
<p>Artificial Intelligence (AI) systems increasingly pervade daily life. New approaches in machine learning combined with the availability of “big data” have enabled substantial advances in computer vision, natural language technologies, recommender systems,
and other sub-fields of AI. </p>
<p>AI-based approaches have the potential for outsized impact on the lives of people with disabilities by combining end-users’ abilities with machine intelligence in harmonious ways. For instance, vision-to-language tools might supplement the perceptual skills
of people who are blind, predictive language technologies might increase communication speeds for people who rely on alternative and augmentative communication devices, and robotic assistants might support manipulation of the physical world by people with
limited mobility. </p>
<p>However, AI technologies also have the potential to stereotype, disadvantage, or exclude people with disabilities, which can contribute to a wide range of negative consequences. Already we see examples of automated hiring software that purports to analyze
facial expression and prosody that may perpetuate ableist assumptions in employment practices, “black box” algorithms for determining who is eligible for disability benefits that make it difficult to challenge bureaucratic decision-making, ad targeting tools
that may make inferences about sensitive demographic traits including age and medical conditions, and even sensor systems that do not recognize people with differences in their appearance, speech, or speed as human.
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<p>This Special Issue of TACCESS will address the myriad ways in which AI FATE (Fairness, Accountability, Transparency, and Ethics) issues intersect with issues relating to disability and accessibility. This includes concerns regarding AI systems designed specifically
for accessibility scenarios (e.g., sign language recognition), AI tools whose use disproportionately impacts people with disabilities (e.g., tools for determining benefits eligibility), as well as general-purpose AI systems (e.g., ensuring that mainstream
tools are accessible to people with disabilities). We encourage articles that consider user groups made up of people with disabilities (including but not limited to disabilities relating to mobility, vision, speech, hearing, cognition, or others), people with
chronic or acute health conditions (including mental health concerns), and older adults, as well as those considering intersections with other minoritized identities.
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<p>Please see the detailed <a href="https://dl.acm.org/journal/taccess/call-for-papers-2020-2">
call for papers</a> for more information about topics of interest and the submission process.
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<p>Submissions are due on <b>Friday July 24th, 2020</b>. </p>
<p><b>Guest Editors: </b></p>
<p><i>Cynthia L. Bennett (Carnegie Mellon University and Apple) </i></p>
<p><i>Stacy M. Branham (University of California, Irvine) </i></p>
<p><i>Meredith Ringel Morris (Microsoft Research) </i></p>
<p><i>Shari Trewin (IBM Accessibility)</i> <font size="2"><br>
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